Three-dimensional discrete element simulation method for repairing rock fracture by MICP based on viscous fine particles

Abstract

The invention discloses a viscous fine particle-based MICP rock fracture restoration three-dimensional discrete element simulation method, which comprises the following steps: carrying out a direct shear test on a rock sample, obtaining stress data and particle size data of the rock sample in the test process, and establishing a relation model; establishing an initial model of fine particle cementation, setting a scaling coefficient and creating boundary and contact conditions; physical attributes and geometric attributes are given to each sphere, the process of repairing rock fractures by calcium carbonate is simulated under the gravity effect, and a discrete sphere set within the boundary range is stored as a first model and placed into a particle attribute giving module; simulating calcium carbonate precipitation; gradually loading extrusion force, detecting the stability of the model by utilizing a balance force function, storing the model as a model II, and putting the model II into a shear loading module; and evaluating a reinforcement effect and judging a failure mode. According to the method, the biological rock fracture repairing effect and the numerical simulation of the damage state can be quickly and flexibly predicted at low cost.

Description

Technical Field

[0001] The present invention relates to the field of rock fissure research, and in particular to a three-dimensional discrete element simulation method for repairing rock fissures using MICP based on viscous fine particles. Background Art

[0002] Rock surfaces often contain cracks and pores. The penetration of these cracks can lead to disasters such as landslides and collapses. Research on how to strengthen rock cracks has become a key topic in geotechnical engineering. Traditionally, chemical grouting has been used to strengthen rock cracks, but the contamination caused by chemical grouting materials is difficult to resolve.

[0003] Since the recognition of its enormous potential in engineering applications, biogeotechnical engineering has become a hot research topic in geotechnical engineering. Microbially induced carbonate precipitation (MICP) technology has shown excellent results in improving the mechanical properties of geotechnical materials and strengthening them, making it a current research focus in biogeotechnical engineering. MICP utilizes the metabolic activity of Sporosarcina pasteurii to form calcium carbonate precipitates, effectively reinforcing rock fractures. Existing research has revealed a series of insights into the bioreinforcement effects and failure modes of rock fractures. For example, during the reinforcement process, factors such as urea and calcium chloride concentrations, fracture roughness, and aperture have a significant impact on the reduction in fractured rock permeability, with urea concentration being particularly important. Generally, rock fractures reinforced with MICP exhibit excellent mechanical properties. Studies have shown that after 10 cycles of grouting, rock fracture surfaces are well sealed, permeability decreases by two orders of magnitude, shear stress increases by 26% to 40%, and shear stiffness increases by 70%. However, existing MICP crack reinforcement research lacks a 3D micromechanical model based on the Discrete Element Method (DEM), making it impossible to analyze the failure mechanism of cementing particles and the evolution of interfacial bonding. At the same time, there are still great cost and technical issues in the on-site application of MICP repair technology, and large-scale rock crack repair experiments are relatively difficult.

[0004] For the treatment of rock fractures, it is crucial to determine whether the repaired fractures can provide a certain shear strength. Therefore, in order to obtain the shear resistance characteristics of rock fracture bioremediation and thereby determine the failure mode and reinforcement effect, a new method is needed that can simultaneously simulate the effect of MICP on rock fracture reinforcement and the failure effect of rock fractures under shear.

[0005] Currently, there is no 3D DEM model for bioremediation of rock fractures in MICP. Current MICP reinforcement models cannot predict the microscopic cementation failure mechanism. There is also a lack of a low-cost, rapid numerical method for predicting the effectiveness of microbial repair of rock fractures. Large-scale rock restoration experiments face problems such as high experimental costs and long cycles. Summary of the Invention

[0006] In response to the above-mentioned deficiencies in the prior art, the present invention provides a three-dimensional discrete element simulation method for MICP repair of rock cracks based on viscous fine particles, which solves the problem of simulating the destruction form and reinforcement effect of biological repair of rock cracks under complex microscopic modes.

[0007] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0008] A three-dimensional discrete element simulation method for MICP repair of rock cracks based on viscous fine particles is provided, which includes the following steps:

[0009] S1: Prepare in-situ rock specimens according to the specifications, conduct direct shear tests on the rock specimens, and obtain the force data of the rock specimens during the test. Measure the calcium carbonate precipitation between rock cracks using an electron microscope to obtain its average particle size, particle size distribution, particle number, and degree of dispersion. Establish a relationship model between normal force and tangential force based on the Mohr-Coulomb criterion.

[0010] S2: Establish an initial model for fine-grained cementation, using spheres within the initial model to represent calcium carbonate particles, set scaling factors, and create boundaries. Based on the radius of the spheres, establish contact conditions between the spheres and between the spheres and the boundaries.

[0011] S3: Assign physical and geometric properties to each sphere, simulate the process of calcium carbonate repairing rock cracks under the effect of gravity, and remove spheres outside the boundary range; save the discrete sphere set within the boundary range as model 1 and place it in the particle property assignment module;

[0012] S4: Reset the physical properties of the sphere in Model 1 to the specified values, assign the preliminary properties of the direct shear test, overwrite the physical properties of the sphere in Model 1, obtain the friction angle of the in-situ rock and input it into the particle property assignment module to simulate calcium carbonate precipitation;

[0013] S5: Based on the servo control function, the upper and lower loading plates are gradually loaded with extrusion force, and the stability of the model is detected using the balance force function. The stable state is saved as model 2 and placed in the shear loading module;

[0014] S6: Call Model 2 in the shear loading module, set the strain rate, record the shear strain generated by Model 2, the stress of the upper and lower loading plates, and the number of spheres that break in contact, evaluate the reinforcement effect, and determine the failure mode.

[0015] Furthermore, step S1 includes:

[0016] S11: Prepare in-situ rock samples according to the specifications, conduct direct shear tests on the rock samples, and record the normal force σ and tangential force τ applied to the rock samples during the test;

[0017] S12: According to the Mohr-Coulomb criterion, the relationship model between the normal force σ and the tangential force τ is constructed:

[0018] S13: Based on the relationship model between normal force σ and tangential force τ, draw the Coulomb envelope of the rock sample. The x-axis of the coordinate system where the Coulomb envelope is located is the internal friction angle of the rock sample. c is the cohesion of the rock sample;

[0019] S14: Use an electron microscope to measure the average particle size and particle size distribution of calcium carbonate precipitates between rock cracks, and calculate the number and dispersion of calcium carbonate precipitates.

[0020] Furthermore, step S2 includes:

[0021] S21: Establish an initial model for fine particle cementation. The initial model is a box model. The spheres within the initial model represent calcium carbonate particles. Create the boundaries of the initial model and set the scaling factors for the model and particles. The four surface boundaries around the initial model serve as wall models, and the upper and lower surface boundaries serve as loading plates.

[0022] S22: According to the coordinate vectors of the spheres in the initial model, the geometric contact information between the spheres is detected, the contact relationship between the spheres is obtained, and the contact relationship between any two spheres satisfies:

[0023] ||C2-C1|| <r2+r1;

[0024] Where C2 and C1 are the coordinate vectors of the centers of any two spheres, r2 and r1 are the radii of any two spheres, and ||.|| is the Euclidean norm of the distance between the spheres.

[0025] S23: Determine the normal vector n and contact point p of the contact between the spheres;

[0026]

[0027] Where δ is the distance between the spheres, δ = r2 + r1 - ||C2 - C1||. If the maximum value of the distance δ is greater than 0, it is determined that the spheres are in contact.

[0028] S24: The contact condition between the sphere and the boundary of the initial model is satisfied;

[0029]

[0030] Where d is the distance between the center of the sphere and the boundary, is the coordinate vector of the center of the sphere closest to the boundary, P closest is the coordinate vector of the point on the boundary closest to the sphere, and r is the radius of the sphere.

[0031] Furthermore, step S3 includes:

[0032] S31: Model based on the relationship between normal force and tangential force Obtain the internal friction angle and cohesion of the sphere, assign physical properties to each sphere, and make the normal stiffness of the sphere equal to the tangential stiffness. The physical properties of the sphere include contact modulus, internal friction angle, cohesion, and density of the sphere;

[0033] S32: assigning geometric parameters of the spheres in the initial model based on the average particle size, particle size distribution and dispersion, the geometric parameters including sphere size and particle size dispersion;

[0034] S33: Set the gravity effect so that the spheres in the initial model fall to the bottom under the action of gravity. After the spheres reach equilibrium, remove the spheres outside the boundary range and apply the set confining pressure. Then remove the gravity effect and adjust the friction between the spheres to simulate the porosity of the rock sample and the process of calcium carbonate repairing rock cracks.

[0035] S34: The discrete sphere set within the boundary range at this time is saved as Model 1, and placed into the particle attribute assignment module.

[0036] Furthermore, step S4 includes:

[0037] S41: Reset the physical properties of the sphere in model 1 to the specified values, assign the preliminary properties of the direct shear test, and overwrite the physical properties of the sphere in model 1;

[0038] S42: Obtain the friction angle and confining pressure of the in-situ rock and input them into the particle attribute assignment module. Remove the wall models corresponding to the four surface boundaries so that the spheres can move freely laterally. Add the bonding force between the spheres and the friction force between the spheres and the loading plate to simulate calcium carbonate precipitation.

[0039] Furthermore, step S5 includes:

[0040] S51: The upper and lower loading plates gradually apply extrusion force through the servo control function, read the displacement of the upper and lower loading plates, and set the loading rate of the loading plates to 0.05 times the distance between the upper and lower loading plates. The stability of the model is tested using the balance force function.

[0041]

[0042] Among them, F is the stability coefficient, Fi is the resultant force on the sphere, i is the sphere number, n is the number of spheres, and F c is the force at the contact point, c is the contact point number, and C is the number of contact points.

[0043] S52: Set the stability threshold F0. If F < F0, it is considered that the reset model has stabilized, and the movement of the upper and lower loading plates is stopped. Otherwise, the upper and lower loading plates continue to move at the loading rate until the reset model stabilizes;

[0044] S53: Save the stable state as Model 2 and place it in the shear loading module.

[0045] Further, step S6 includes:

[0046] S61: Retrieve Model 2 in the shear loading module, set the strain rate generated in the x direction, drive Model 2 to generate strain based on the set strain rate, save the intermediate state every time the strain of Model 2 reaches 0.001, and record the shear strain in the x and y directions, the stress of the upper and lower loading plates, and the number of spheres with contact fractures;

[0047] S62: Read the filling degree, peak shear strength, and stress-strain curve, evaluate the reinforcement effect through the filling degree and peak shear strength, and judge the failure mode based on the stress-strain curve.

[0048] The beneficial effects of the present invention are as follows: This solution simulates calcium carbonate precipitation by establishing a three-dimensional model of discrete spheres, and combines the analysis of the microscopic failure process under direct shear tests to reveal the stress-strain relationship, solving the problem of simulating the failure form and reinforcement effect of bioremediation of rock fractures under complex microscopic patterns. The present invention can achieve fast, low-cost, and flexible numerical simulations for predicting the bioremediation effect and failure state of rock fractures, providing a numerical model and reinforcement prediction for on-site practical applications and large-scale rock mass repair estimations. Brief Description of the Drawings

[0049] Figure 1 It is a flowchart of a three-dimensional discrete element simulation method for MICP repair of rock fractures based on viscous fine particles.

[0050] Figure 2 It is a comparison diagram of fracture apertures between experimental data and simulation data.

[0051] Figure 3 It is a demonstration diagram of the failure of a 3D specimen.

[0052] Figure 4 It is a simulation diagram of the shear test on the specimen.

[0053] Figure 5 It is a three-dimensional diagram of the initial model. Detailed Embodiments

[0054] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0055] like Figure 1 As shown, a three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles includes the following steps:

[0056] S1: Prepare in-situ rock samples according to the specifications, conduct direct shear tests on the rock samples, and obtain the force data of the rock samples during the test; measure the calcium carbonate precipitation between the rock cracks using an electron microscope to obtain its average particle size, particle size distribution, particle number and degree of dispersion, and establish a relationship model between normal force and tangential force based on the Mohr-Coulomb criterion. Step S1 specifically includes:

[0057] S11: Prepare an in-situ rock sample according to the specification. In this embodiment, the size of the rock sample is 50 mm × 50 mm × 50 mm. Perform a direct shear test on the rock sample, making the vertical pressure different in each test, and record the normal force σ and tangential force τ applied to the rock sample during the test.

[0058] S12: According to the Mohr-Coulomb criterion, the relationship model between the normal force σ and the tangential force τ is constructed:

[0059] S13: Based on the relationship model between normal force σ and tangential force τ, draw the Coulomb envelope of the rock sample. The x-axis of the coordinate system where the Coulomb envelope is located is the internal friction angle of the rock sample. c is the cohesion of the rock sample;

[0060] S14: Use an electron microscope to measure the average particle size and particle size distribution of calcium carbonate precipitates between rock cracks, and calculate the number and dispersion of calcium carbonate precipitates.

[0061] S2: In this embodiment, the discrete element software Yade is used to establish an initial model of fine particle cementation. Spheres within the initial model are used to represent the particles of the rock sample. A scaling factor is set and a boundary is created. To accelerate the calculation process, the scaling factor of the model and particles is set, generally taking a value of 600. The contact conditions between the spheres and between the spheres and the boundary are established based on the radius of the spheres. Step S2 specifically includes:

[0062] S21: Establish an initial model of fine particle cementation. The initial model is a box model, such as Figure 5As shown in the figure, the spheres in the initial model represent calcium carbonate particles, and the boundary of the initial model is created. The built-in Box class in Yade is used to create the boundary of the rectangular block, generate six loading plates, and set the scaling factors of the model and particles. The four surface boundaries around the initial model serve as wall models, and the upper and lower surface boundaries serve as loading plates.

[0063] S22: According to the coordinate vectors of the spheres in the initial model, the geometric contact information between the spheres is detected to obtain the contact relationship between the spheres. The geometric contact information of the two spheres is detected using Ig2_Sphere_Sphere_ScGeom6D(), and the contact relationship between any two spheres satisfies:

[0064] ||C2-C1|| <r2+r1;

[0065] Where C2 and C1 are the coordinate vectors of the centers of any two spheres, r2 and r1 are the radii of any two spheres, and ||.|| is the Euclidean norm of the distance between the spheres.

[0066] S23: Determine the normal vector n and contact point p of the contact between the spheres;

[0067]

[0068] Where δ is the distance between the spheres, δ = r2 + r1 - ||C2 - C1||. If the maximum value of the distance δ is greater than 0, it is determined that the spheres are in contact.

[0069] S24: Using Ig2_Box_Sphere_ScGeom6D() to detect the contact information between the sphere and the boundary, the contact condition between the sphere and the boundary of the initial model is satisfied;

[0070]

[0071] Where d is the distance between the center of the sphere and the boundary, is the coordinate vector of the center of the sphere closest to the boundary, P closest is the coordinate vector of the point on the boundary closest to the sphere, and r is the radius of the sphere.

[0072] S3: Assign physical and geometric properties to each sphere, simulate the process of calcium carbonate repairing rock cracks under the effect of gravity, and remove spheres outside the boundary range; save the discrete sphere set within the boundary range as model 1 and place it in the particle property assignment module. Step S3 specifically includes:

[0073] S31: Relationship model based on normal force σ and tangential force τ Get the internal friction angle and cohesion of the sphere, and assign physical properties to each sphere. For simplicity, the normal force of the sphere is equal to the tangential force. The physical properties of the sphere include contact modulus, internal friction angle, cohesion and density of the sphere. Use the CohFrictMat() function to assign physical properties to the sphere.

[0074] The physical properties of the sphere in this embodiment at this stage are preset as shown in Table 1:

[0075] Table 1 Preset particle physical parameters

[0076]

[0077] S32: Assign geometric parameters to the spheres in the initial model based on the average particle size, particle size distribution, and dispersion. The geometric parameters include the sphere size and particle size dispersion. The geometric parameters of the spheres are preset as shown in Table 2 below:

[0078] Table 2 Preset particle geometric parameters

[0079]

[0080] S33: Set the gravity effect so that the spheres in the initial model fall to the bottom under the action of gravity. After the spheres reach equilibrium, remove the spheres outside the boundary range and apply a confining pressure of 50 kPa. Then remove the gravity effect to achieve isotropy in the later stage of loading. Adjust the friction between the spheres to simulate the porosity of the rock sample and the process of calcium carbonate repairing rock cracks.

[0081] S34: The discrete sphere set within the boundary range is saved as Model 1 and placed in the particle attribute assignment module. After the initial model generation module is completed, the discrete element sphere set is saved as "Model 1" so that it can be called in the particle attribute assignment module.

[0082] S4: Reset the physical properties of the sphere in Model 1 to the specified values, assign the preliminary properties of the direct shear test, overwrite the physical properties of the sphere in Model 1, obtain the friction angle of the in-situ rock and input it into the particle property assignment module to simulate calcium carbonate precipitation. Step S4 specifically includes:

[0083] S41: Reset the physical properties of the sphere in model 1 to the specified values, assign the preliminary properties of the direct shear test, and overwrite the physical properties of the sphere in model 1;

[0084] S42: Obtain the friction angle of the in-situ rock and input it into the particle attribute assignment module. The wall models corresponding to the four surface boundaries are removed to allow the spheres to move freely laterally. This imparts adhesion between the spheres and friction between the spheres and the loading plate to simulate calcium carbonate precipitation. The parameters related to the sphere physical properties in this stage are as shown in Table 3.

[0085] Table 3 Physical Parameters of the Sphere

[0086]

[0087] S5: Gradually apply extrusion pressure to the upper and lower loading plates based on the servo control function, detect the stability of the model using the balance force function, and save the stable state as Model 2, which is placed into the shear loading module. Step S5 specifically includes:

[0088] S51: The upper and lower loading plates gradually apply extrusion pressure through the servo control function. The extrusion pressure simulates the confining pressure of in-situ rock, read the displacements of the upper and lower loading plates, and make the loading rate of the loading plates 0.05 times the distance between the upper and lower loading plates, and detect the stability of the model using the balance force function;

[0089]

[0090] Among them, F is the stability coefficient, F i is the resultant force on the sphere, i is the number of the sphere, n is the number of spheres, F c is the force at the contact point, c is the number of the contact point, and C is the number of contact points.

[0091] S52: Set the stability threshold F0, which is taken as 0.005 in this embodiment. If F < F0, it is considered that the model has been stable, stop the movement of the upper and lower loading plates, otherwise, the upper and lower loading plates continue to move according to the loading rate until the model is stable; the stability threshold should be as small as possible, and the operation time should be comprehensively considered at the same time.

[0092] S53: Save the stable state as Model 2, as Figure 4 shown, generate a shear specimen model, and place it into the shear loading module for calling in the shear loading module.

[0093] S6: Retrieve Model 2 in the shear loading module, set the strain rate, record the shear strain generated by Model 2, the stress of the upper and lower loading plates, and the number of spheres with contact fractures, evaluate the reinforcement effect, and judge the failure mode. Step S6 specifically includes:

[0094] S61: Retrieve Model 2 in the shear loading module, set the strain rate generated along the x direction, drive Model 2 to generate strain based on the set strain rate, save an intermediate state every time the strain of Model 2 reaches 0.001, and record the shear strain in the x direction and y direction, the stress of the upper and lower loading plates, and the number of spheres with contact fractures;

[0095] S62: Read the filling degree, peak shear strength, and stress-strain curve, evaluate the reinforcement effect through the filling degree and peak shear strength, and judge the failure mode through the stress-strain curve.

[0096] In this embodiment, based on the experimental data of the direct shear test, a stress-strain curve is generated in yade as shown in FIG. Figure 2 As shown, export it into a vtk file, and import the vtk file into the paraview software to see the complete failure process and strain diagram, as shown in Figure 3 shown.

[0097] This embodiment relies on the Yade platform, that is, the three-dimensional module of YADE. In the software, spheres are regarded as calcium carbonate particles, and calcium carbonate particles are regarded as rigid particles. The software allows overlap between particles to simulate the contact force between particles. Based on Newton's second law, the destruction between contacting particles can be divided into two modes: shear and opening. After the contact relationship between the particles is destroyed, the mechanical properties will change from linear to nonlinear, which means that the change in the contact state of the particles determines the constitutive relationship of the particles. Therefore, Yade does not need to set macroscopic constitutive models and parameters. These characteristics will be obtained from the mechanical and geometric properties of the particles.

[0098] This method simulates calcium carbonate precipitation by building a three-dimensional model of discrete spheres. Combined with analysis of the microscopic failure process under direct shear testing, it reveals stress-strain relationships and addresses the challenge of simulating the failure modes and reinforcement effects of bioremediation of rock fractures under complex microscopic models. This method enables rapid, low-cost, and flexible numerical simulations for predicting the repair effects and failure states of bioremediation of rock fractures, providing numerical models and reinforcement predictions for field applications and large-scale rock restoration estimates.

Claims

1. A three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles, characterized by: The following steps are involved: S1: Prepare in-situ rock specimens according to the specifications, conduct direct shear tests on the rock specimens, and obtain the force data of the rock specimens during the test. Measure the calcium carbonate precipitation between rock cracks using an electron microscope to obtain its average particle size, particle size distribution, particle number, and degree of dispersion. Establish a relationship model between normal force and tangential force based on the Mohr-Coulomb criterion. S2: Establish an initial model for fine-grained cementation, using spheres within the initial model to represent calcium carbonate particles, set scaling factors, and create boundaries. Based on the radius of the spheres, establish contact conditions between the spheres and between the spheres and the boundaries. S3: Assign physical and geometric properties to each sphere, simulate the process of calcium carbonate repairing rock cracks under the effect of gravity, and remove spheres outside the boundary range; save the discrete sphere set within the boundary range as model 1 and place it in the particle property assignment module; S4: Reset the physical properties of the sphere in Model 1 to the specified values, assign the preliminary properties of the direct shear test, overwrite the physical properties of the sphere in Model 1, obtain the friction angle of the in-situ rock and input it into the particle property assignment module to simulate calcium carbonate precipitation; S5: Based on the servo control function, the upper and lower loading plates are gradually loaded with extrusion force, and the stability of the model is detected using the balance force function. The stable state is saved as model 2 and placed in the shear loading module; S6: Call Model 2 in the shear loading module, set the strain rate, record the shear strain generated by Model 2, the stress of the upper and lower loading plates, and the number of spheres that break in contact, evaluate the reinforcement effect, and determine the failure mode.

2. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 1 is characterized in that: The step S1 comprises: S11: Prepare in-situ rock samples according to the specifications, conduct direct shear tests on the rock samples, and record the normal force σ and tangential force τ applied to the rock samples during the test; S12: According to the Mohr-Coulomb criterion, the relationship model between the normal force σ and the tangential force τ is constructed: S13: Based on the relationship model between normal force σ and tangential force τ, draw the Coulomb envelope of the rock sample. The x-axis of the coordinate system where the Coulomb envelope is located is the internal friction angle of the rock sample. c is the cohesion of the rock sample; S14: Use an electron microscope to measure the average particle size and particle size distribution of calcium carbonate precipitates between rock cracks, and calculate the number and dispersion of calcium carbonate precipitates.

3. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 2 is characterized in that: The step S2 comprises: S21: Establish an initial model for fine particle cementation. The initial model is a box model. The spheres within the initial model represent calcium carbonate particles. Create the boundaries of the initial model and set the scaling factors for the model and particles. The four surface boundaries around the initial model serve as wall models, and the upper and lower surface boundaries serve as loading plates. S22: According to the coordinate vectors of the spheres in the initial model, the geometric contact information between the spheres is detected, the contact relationship between the spheres is obtained, and the contact relationship between any two spheres satisfies: ||C2-C1|| <r2+r1; Where C2 and C1 are the coordinate vectors of the centers of any two spheres, r2 and r1 are the radii of any two spheres, and ||.|| is the Euclidean norm of the distance between the spheres. S23: Determine the normal vector n and contact point p of the contact between the spheres; Where δ is the distance between the spheres, δ = r2 + r1 - ||C2 - C1||. If the maximum value of the distance δ is greater than 0, it is determined that the spheres are in contact. S24: The contact condition between the sphere and the boundary of the initial model is satisfied; Where d is the distance between the center of the sphere and the boundary, is the coordinate vector of the center of the sphere closest to the boundary, P closest is the coordinate vector of the point on the boundary closest to the sphere, and r is the radius of the sphere.

4. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 3 is characterized in that: The step S3 comprises: S31: Model based on the relationship between normal force and tangential force Obtain the internal friction angle and cohesion of the sphere, assign physical properties to each sphere, and make the normal stiffness of the sphere equal to the tangential stiffness. The physical properties of the sphere include contact modulus, internal friction angle, cohesion, and density of the sphere; S32: Assign geometric parameters to the spheres within the initial model based on the average particle size, particle size distribution, and degree of dispersion. The geometric parameters include sphere size and particle size dispersion; S33: Set the gravity effect so that the spheres within the initial model fall to the bottom under the action of gravity. After the spheres reach the equilibrium state, remove the spheres outside the boundary range, apply a set confining pressure, then remove the gravity effect, and adjust the friction between the spheres to simulate the porosity of the rock specimen and the process of calcium carbonate repairing rock fractures; S34: Save the discrete sphere set within the boundary range at this time as Model 1 and place it into the particle property assignment module.

5. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 4 is characterized in that: The steps S4 include: S41: Reset the physical properties of the spheres in Model 1 to the specified values, assign the preparatory properties for the direct shear test, and overwrite the physical properties of the spheres in Model 1; S42: Obtain the friction angle of the in-situ rock and input it into the particle property assignment module. Remove the wall models corresponding to the four surface boundaries so that the spheres can move freely laterally. Assign the cohesive force between the spheres and the friction force between the spheres and the loading plate to simulate calcium carbonate precipitation.

6. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 5 is characterized in that: The steps S5 include: S51: The upper and lower loading plates gradually apply extrusion force through the servo control function. The extrusion force simulates the confining pressure of the in-situ rock. Read the displacements of the upper and lower loading plates, and make the loading rate of the loading plates 0.05 times the distance between the upper and lower loading plates. Use the balance force function to detect the stability of the model; Among them, F is the stability coefficient, F i is the net force on the sphere, i is the number of the sphere, n is the number of spheres, F c is the force on the contact point, c is the number of the contact point, and C is the number of contact points. S52: Set the stability threshold F0. If F < F0, it is considered that the reset model has become stable, and stop the movement of the upper and lower loading plates. Otherwise, the upper and lower loading plates continue to move at the loading rate until the reset model becomes stable; S53: Save the stable state as Model 2 and place it into the shear loading module.

7. The three-dimensional discrete element simulation method for repairing rock cracks based on MICP of viscous fine particles according to claim 6 is characterized in that: The steps S6 include: S61: Retrieve Model 2 from the shear loading module, set the strain rate generated in the x direction, drive Model 2 to generate strain based on the set strain rate. Save the intermediate state once every time the strain of Model 2 reaches 0.001, and record the shear strains in the x and y directions, the stresses of the upper and lower loading plates, and the number of spheres with contact fractures; S62: Read the filling degree, peak shear strength, and stress-strain curve, and evaluate the reinforcement effect through the filling degree and peak shear strength, and judge the failure mode based on the stress-strain curve.

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