Numerical simulation method of discrete element for splitting grouting based on time-varying characteristics of slurry viscosity

Abstract

The present application proposes a splitting grouting discrete element numerical simulation method based on the time-varying characteristics of slurry viscosity, belonging to the technical field of splitting grouting simulation; including obtaining the time-varying characteristics of slurry viscosity by conducting indoor test of time-varying characteristics of slurry viscosity; constructing a slurry DEM particle viscosity time-varying contact model based on the time-varying characteristics; conducting splitting grouting simulation based on the slurry DEM particle viscosity time-varying contact model; comparing the obtained simulation results with the test results of indoor test under fixed working conditions, and calibrating the slurry DEM particle contact model; using the calibrated slurry DEM particle contact model to conduct splitting grouting simulation under multiple working conditions. The present application can effectively couple the time-varying characteristics of slurry viscosity and the phase change consolidation mechanism, realize accurate simulation of the dynamic influence of the rheological properties of the slurry in the pore on the splitting diffusion process, and further provide a beneficial method for improving the accuracy and scientificity of the splitting grouting diffusion process of tunnels and underground engineering.

Description

Technical Field

[0001] This invention belongs to the field of split grouting simulation technology, and particularly relates to a discrete element numerical simulation method for split grouting based on the time-varying characteristics of grout viscosity. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] As tunnel construction continues to expand, projects are advancing into deeper, more complex strata, including those with high ground stress and water-rich, weak surrounding rock. This leads to frequent geological disasters such as mudslides and water inrushes, seriously threatening construction safety and project stability. In areas with even more complex geological conditions, weak rock strata are more prone to instability and failure. To address these challenges, key technologies such as advanced geological forecasting, intelligent monitoring, and grouting reinforcement are being continuously strengthened. In particular, the widespread application of fracturing grouting technology in water inrush disaster management can provide strong support for tunnel construction in complex strata, enhancing the safety and resilience of infrastructure construction.

[0004] Water-rich, weak surrounding rock is composed of granular soil with fine, dispersed pores, consistent with the characteristics of pore-filled media. Due to poor pore connectivity, groundwater resides within these pore spaces, making it susceptible to sudden pressure changes due to external disturbances. During tunnel excavation, the redistribution of stress in the surrounding rock caused by excavation disturbances can easily lead to increased pore water pressure, resulting in rock mass structural damage and potentially triggering mudslides and water inrushes. This risk is particularly high in areas with high ground stress or poor geological stability, necessitating measures such as grouting reinforcement to enhance surrounding rock stability and ensure construction safety.

[0005] Fracturing grouting diffusion mode is a key method in grouting reinforcement engineering, particularly suitable for reinforcing weak surrounding rock and fractured rock masses. Under high pressure, the grout overcomes the constraint stress of the surrounding rock, expands along micro-fractures, and forms fracturing channels. After the grout solidifies, it forms a fracturing grout vein skeleton in the injected medium, which can improve the overall strength and impermeability of the rock mass. Compared with permeable grouting, fracturing grouting is more suitable for low-permeability strata and exhibits superior reinforcement effects under complex geological conditions. It is widely used in mudslide and water inrush disaster control and tunnel stability control.

[0006] However, the diffusion process of fracturing grout is a black box process in both laboratory and field tests, and cannot be directly observed. Grout flow characteristics are affected by formation heterogeneity, stress state, and grout properties, making precise control and prediction difficult. While transparent soil tests can simulate grout propagation, their material mechanical properties differ significantly from those of real formations, failing to accurately reproduce the diffusion pattern of grout under complex geological conditions. Furthermore, transparent soil tests have stringent experimental requirements, making it difficult to accurately reflect actual engineering conditions, and their results have certain limitations, affecting a deeper understanding of the diffusion and reinforcement mechanisms of fracturing grout.

[0007] Due to its invisibility and complex fluid-structure interaction characteristics, the diffusion and reinforcement mechanism of fracturing grout is often studied using numerical simulation methods to reveal the grout propagation mechanism and optimize grouting design. However, common methods such as the finite element method (FEM), finite volume method (FVM), and fluid volume method (VOF) have limitations in fracturing grouting simulation. For example, FEM, based on the assumption of a continuous medium, struggles to accurately describe discrete fractures in rock mass and the discontinuous propagation characteristics of grout, affecting the accurate simulation of grout migration paths; while FVM is suitable for fluid conservation problems, its ability to characterize non-uniform grout penetration and fracturing processes is limited and easily affected by mesh generation; VOF is mainly used for free interface flow simulation and struggles to effectively describe the mechanical effects of grout on the injected medium and the evolution of fracturing channels. In contrast, the Discrete Element Method (DEM), based on the particle discrete body assumption, can naturally simulate the initiation and expansion of fracturing channels and the fracturing-compacting process of grout on the injected medium. It can dynamically track the stress evolution of grout-rock interaction, is suitable for grouting simulation of highly heterogeneous strata, and provides a more refined mechanical model expression for fracturing grouting under complex geological conditions.

[0008] Therefore, even though there are many existing methods for numerical simulation of fracturing grouting, these methods all have the following technical problems:

[0009] (1) The time-varying effect of slurry viscosity was ignored. Ignoring the time-varying effect of slurry viscosity can lead to simulation deviations in flowability and diffusion range. The initial viscosity of the slurry is low and the diffusion is rapid, followed by an increase in viscosity and eventual solidification. If the numerical simulation adopts the assumption of constant viscosity, the diffusion range may be overestimated or underestimated, affecting the prediction of the reinforced area. For example, if the viscosity is too low, the simulation results may exaggerate the slurry penetration range; if the viscosity is too high, the initial diffusion capacity of the slurry may be underestimated.

[0010] (2) The phase change process of the slurry cannot be accurately described. The inability to accurately describe the phase change process of the slurry will affect the simulation of the consolidation mechanism. The slurry gradually transforms from a liquid state to a gel state and then consolidates. If the numerical simulation does not consider this evolution process and instead assumes that the slurry maintains a fixed viscosity, it will be impossible to truly reproduce its solidification process, resulting in a distortion in the evaluation of the reinforcement effect such as mechanical strength and load-bearing capacity.

[0011] (3) The time-varying effect of grout viscosity is ignored, which affects the interaction between the grout and the surrounding rock. As viscosity increases, the grout's permeability decreases and its diffusion pattern changes, thus affecting the degree of fracture filling and the reinforcement effect. If this factor is not considered in the simulation, the distribution range of the grout in the fracture may be overestimated, thereby affecting the assessment of engineering safety and stability. Therefore, in the numerical simulation of fracturing grouting, it is crucial to reasonably couple the time-varying characteristics of grout viscosity. Summary of the Invention

[0012] To overcome the shortcomings of the prior art, this invention provides a discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity. This method can effectively couple the time-varying characteristics of grout viscosity and the phase transformation consolidation mechanism, and realize the effective simulation of the dynamic influence of the rheological characteristics of grout in the pore-filled medium on the splitting diffusion process. This provides effective guidance for improving the scientificity and applicability of grouting reinforcement design for tunnels and underground engineering.

[0013] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0014] This invention provides a discrete element numerical simulation method for split grouting based on the time-varying characteristics of grout viscosity.

[0015] A discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity includes:

[0016] Indoor tests were conducted on the time-varying characteristics of slurry viscosity, and the time-varying characteristics of slurry viscosity were obtained based on the test results.

[0017] Based on the obtained time-varying characteristics, a particle contact model of slurry DEM is constructed; and fracturing grouting simulation is performed based on the constructed slurry DEM particle contact model.

[0018] Under fixed working conditions, the simulation results obtained from the split grouting simulation were compared with the test results from the laboratory test, and the grout DEM particle contact model was calibrated based on the comparison results.

[0019] Using the calibrated grout DEM particle contact model, we conducted fracturing grouting simulations under multiple working conditions.

[0020] Furthermore, the indoor tests include: cement paste funnel flowability test, cement paste plate flowability test, and slurry viscosity time-varying characteristic paddle rotor test.

[0021] Furthermore, in the cement paste funnel fluidity test, the change in the time it takes for the paste to flow out of the standard funnel is used to characterize the viscosity growth characteristics.

[0022] In the cement paste plate fluidity test, the limiting effect of slurry viscosity growth on the spread is obtained by measuring the spread diameter of the slurry on the plate.

[0023] In the time-varying viscosity test of the paddle rotor, the viscosity change curve of the slurry over time is plotted by measuring the shear viscosity of the slurry at different time points.

[0024] Furthermore, the construction of the slurry DEM particle contact model includes: simulation of the injected medium environment, servo-driven stress loading, slurry particle generation, particle parameter assignment, multi-field physical information monitoring, design of time-varying initial conditions for slurry viscosity, traversal of global particle contact parameters, determination and iterative update of time-varying characteristics of slurry viscosity, critical conditions for slurry phase change, and update of strength enhancement after initial setting of slurry veins.

[0025] Furthermore, based on the simulation of the injected medium environment, a numerical model of the porous medium that conforms to the actual geological conditions is constructed; during the multi-field physical information monitoring process, the detected physical information includes the changes in grout pressure, grouting volume, and porosity between injected media during the grout diffusion process.

[0026] Furthermore, when traversing the global particle contact parameters, the contact parameter assignment command based on the discrete element method is used to gradually adjust the interparticle forces using a trial-and-error method to simulate the diffusion pattern of slurry in porous media; the time-varying characteristics of slurry viscosity are determined and iteratively updated, that is, the slurry viscosity parameters are dynamically adjusted according to the slurry flow state and shear stress conditions to make the simulation results consistent with the actual grouting process.

[0027] Furthermore, the critical condition for phase change of the slurry is set based on the initial setting time and rheological properties of the slurry.

[0028] Furthermore, under fixed working conditions, the simulation results obtained from the splitting grouting simulation were compared with the test results from the laboratory test; the test results obtained from the laboratory test included morphological results, physical property results, and mechanical property results.

[0029] Furthermore, the morphological results obtained are as follows: under the fixed working conditions in the physical test, the results of the high-pressure splitting grouting test are observed to obtain the morphology of grout splitting and diffusion, and the development direction, maximum diffusion range and average width of grout veins of grout splitting and diffusion are measured.

[0030] The obtained physical properties results are as follows: In terms of the overall physical properties of the grouting solid, the tests include permeability and density;

[0031] The obtained mechanical properties are as follows: the strength and deformation characteristics of the reinforced body are evaluated using triaxial compression tests and direct shear tests.

[0032] Furthermore, the multiple working conditions include ground stress conditions, grouting pressure, and grout mix ratio.

[0033] The above one or more technical solutions have the following beneficial effects:

[0034] (1) This invention can dynamically simulate the time-varying characteristics of grout viscosity. Based on the time-varying characteristics of grout viscosity obtained from indoor experiments, this invention constructs a grout DEM particle contact model; and performs fracturing grouting simulation based on the constructed grout DEM particle contact model. By introducing a simulation method for the change of grout viscosity over time, it is possible to more scientifically and accurately depict the influence of the phase transition process of grout at different injection stages (from low viscosity to high viscosity) and from liquid to gel to solidification on the fracturing diffusion process. This is of great significance for improving the prediction of grout fluidity and the evaluation of reinforcement effect under complex geological conditions, and breaks through the limitation of traditional DEM numerical simulation methods that cannot fully consider the time-varying characteristics of viscosity.

[0035] (2) This invention combines the discrete element method with experimental data to optimize the particle contact model of grout DEM: By developing a highly adaptable contact model in the discrete element method, the diffusion process of grout in porous media can be accurately simulated, i.e., the time-varying characteristics of parameters such as the adhesion force and flow resistance between grout particles. This optimization makes the simulation results closer to the actual situation, thus providing a more reliable numerical basis for grouting reinforcement design. By numerically simulating the evolution of this change, the phase change process of grout can be accurately described.

[0036] (3) Under fixed working conditions, this invention compares the simulation results obtained from the fracturing grouting simulation with the test results from the laboratory test, and calibrates the grout DEM particle contact model based on the comparison results; using the calibrated grout DEM particle contact model, fracturing grouting simulation under multiple working conditions is carried out. This invention ensures the accuracy and reliability of numerical simulation by monitoring and verifying multiple physical information, that is, by comparing and verifying the results based on the physical test and simulation results. By comparing the fracturing grout flow rate and pressure evolution law with the time measured in the physical test, as well as the final fracturing diffusion morphology and the overall physical and mechanical properties of the reinforced body, the rationality of the simulation results is verified. This provides a strong scientific basis for grouting reinforcement in actual engineering and helps to guide tunnel construction and safety reinforcement under complex geological conditions. At the same time, the calibration of the model, the consideration of multiple working conditions, and the comparison of multiple test results can better reflect the influence of the time-varying effect of grout viscosity on the interaction between grout and surrounding rock, thereby providing a better guarantee for the safety and stability assessment of the project.

[0037] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0038] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0039] Figure 1 This is a flowchart of the discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of slurry viscosity in Embodiment 1 of the present invention.

[0040] Figure 2 This is a schematic diagram of the time-varying parameters of the splitting slurry viscosity in Embodiment 1 of the present invention.

[0041] In the figure, 1. The medium injected into the pores; 2. The vertical stress servo loading boundary; 3. The horizontal stress servo loading boundary; 4. The grouting pipe boundary; 5. The fracturing grout injection channel; 6. The surface viscosity parameters between grout particles; 7. The grout outlet; 8. The development direction of the fracturing grout. Detailed Implementation

[0042] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. 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 invention pertains.

[0043] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0044] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0045] The overall concept proposed in this invention is as follows: the time-varying effect of grout viscosity is an important property of grouting materials, directly affecting the grout's fluidity, diffusion range, and the final reinforced mechanical properties of the injected medium. During injection, the grout typically undergoes a dynamic evolution from low to high viscosity, followed by phase transformation and consolidation. Therefore, numerical simulations must accurately describe this complex time-varying process to reflect the grout's diffusion mechanism and reinforcement effect in the surrounding rock. However, existing discrete element method (DEM) simulations of grout fracturing and diffusion still face significant technical challenges. DEM is primarily applicable to the motion and contact mechanics calculations of discrete particles; existing techniques struggle to accurately represent the phase transformation process of grout from liquid to gel and then to consolidation. Furthermore, DEM relies on particle interaction models, but existing models still have limitations in describing the time-varying viscosity of grout, changes in rheological properties, and the interaction between the grout and the surrounding rock interface. Therefore, effectively coupling the time-varying characteristics of grout viscosity and the phase transformation and consolidation mechanism within the DEM framework remains a critical problem to be solved in numerical simulation research of fracturing grouting. Therefore, the discrete element numerical simulation method for splitting grouting based on the time-varying viscosity of grout proposed in this invention effectively characterizes the dynamic influence of the rheological properties of grout in porous media on the splitting diffusion process, breaking through the limitation of existing discrete element methods in describing the phase change process of grout. It provides a more accurate numerical calculation means for the study of splitting grouting mechanism under complex geological conditions, improves the scientificity and applicability of grouting reinforcement design for tunnels and underground engineering, and has beneficial engineering application value and theoretical guiding significance.

[0046] Example 1

[0047] This embodiment discloses a discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity. Based on discrete element (DEM) theory and combined with experimental results of the flowability and time-varying characteristics of different types of grout in laboratory tests, this method further develops a contact model for the time-varying characteristics of grout viscosity. This enables effective simulation of the dynamic influence of grout rheological properties on the splitting diffusion process in porous grouting media. This invention provides a reference approach for the effective expression of the time-varying characteristics of grout viscosity and the phase transformation consolidation mechanism in discrete element simulation methods for splitting grouting in porous media.

[0048] like Figure 1 As shown, the discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity includes:

[0049] Step S1: Conduct indoor tests on the time-varying characteristics of slurry viscosity, and obtain the time-varying characteristics of slurry viscosity based on the test results;

[0050] Step S2: Based on the obtained time-varying characteristics, construct a particle contact model of the slurry DEM; perform fracturing grouting simulation based on the constructed slurry DEM particle contact model;

[0051] Step S3: Under fixed working conditions, compare the simulation results obtained from the split grouting simulation with the test results from the indoor test, and calibrate the grout DEM particle contact model based on the comparison results.

[0052] Step S4: Using the calibrated grout DEM particle contact model, perform fracturing grouting simulation under multiple working conditions.

[0053] Based on the above method, this invention can effectively couple the time-varying characteristics of grout viscosity and the phase change consolidation mechanism, achieving effective simulation of the dynamic influence of grout rheological properties on the splitting and diffusion process in the pore-filled medium; thus providing effective guidance for improving the scientificity and applicability of grouting reinforcement design for tunnels and underground engineering. To facilitate understanding of the technical solution of this invention, the specific implementation methods of this invention will be further explained and described below.

[0054] Step S1: Conduct indoor tests on the time-varying characteristics of slurry viscosity, and obtain the time-varying characteristics of slurry viscosity based on the test results.

[0055] The laboratory tests for the time-varying characteristics of slurry viscosity include: cement paste funnel flowability test, cement paste plate flowability test, and slurry viscosity time-varying characteristic paddle rotor test, used to summarize the time-varying characteristics of slurry viscosity. Specifically, this can be achieved through steps S101-S104:

[0056] Step S101: Cement paste funnel flowability test.

[0057] The initial fluidity and thickening trend of cement paste over time can be quickly obtained by measuring the fluidity of the paste using a funnel. In the experiment, the change in the time it takes for the paste to flow out of the standard funnel reflects its viscosity growth characteristics, thus characterizing the rheological behavior of the paste in the initial stage of grouting.

[0058] As an optional embodiment, the cement paste funnel flowability test can be used to evaluate the initial fluidity and rheological changes of the paste over time. Specifically, the test uses a standard outflow funnel to measure the outflow time of a certain volume of paste through the funnel opening; a shorter outflow time indicates better initial fluidity of the paste, while an increase in outflow time reflects the gradual thickening of the paste. This test can quantitatively characterize the thixotropy and early setting tendency of the paste, providing basic data for simulating time-varying viscosity characteristics.

[0059] Step S102: Cement paste plate fluidity test.

[0060] The cement paste plate flowability test is used to determine the spreadability of the paste at different time points, thereby characterizing the effect of increased paste viscosity on its flow range. In the test, the limiting effect of increased paste viscosity on its spreadability can be obtained by measuring the diameter of the paste spread on the plate.

[0061] As an optional embodiment, the cement paste flat plate flowability test can be used to determine the spreadability of the paste on a horizontal surface to evaluate its consistency and time dependence. Specifically, in the test, the paste is inverted on a standard glass or metal plate, forming a circular diffusion area under its own gravity. The flowability of the paste is determined by measuring the change in the diffusion diameter. A higher initial flowability indicates a thinner paste, while a gradually decreasing diffusion diameter over time indicates increased rheological properties and a gradual increase in viscosity. This test method is suitable for pastes with low water-cement ratios and can visually reflect the trend of viscosity change over time.

[0062] Step S103: Time-varying characteristics of slurry viscosity test using a paddle rotor.

[0063] The time-varying viscosity characteristics of slurry can be directly measured by a paddle rotor, which directly measures the shear viscosity of the slurry at different time points. This allows for an accurate depiction of the viscosity change curve of the slurry over time, providing key parameter support for numerical simulation.

[0064] The time-varying viscosity characteristic test of slurry using a paddle rotor is a precise method for directly determining slurry viscosity. In practical applications, by rotating the paddle rotor, the viscosity changes of the slurry at different shear rates can be measured, thereby analyzing the shear thinning or shear thickening characteristics of the slurry and quantifying the time-varying viscosity change before solidification. This test can provide a viscosity evolution curve of the slurry from its initial state to its final solidification, providing key input parameters for numerical simulations.

[0065] Step S104: Summary of time-varying characteristics of slurry viscosity.

[0066] The above three tests can accurately calibrate the contact characteristics between slurry particles in discrete element simulations, such as interparticle adhesion and flow resistance, to ensure that the simulated slurry diffusion process matches the actual situation. This calibration method enables the discrete element simulation structure to realistically reflect the mechanical behavior of slurry splitting and diffusion, improving the reliability of the simulation results.

[0067] Based on the experimental results of steps S101-S104, the time-varying characteristics of grout viscosity can be summarized as follows: The grout exhibits low viscosity and high fluidity in the initial stage. As time progresses, hydration occurs, and the internal structure gradually forms and strengthens, leading to increased viscosity and decreased fluidity. The rate of viscosity increase is closely related to the water-cement ratio, admixtures, and additive types. Using experimental data, a time-varying mathematical model of grout viscosity can be established, providing accurate physical property parameter inputs for numerical simulation of fracturing grouting. This model can also guide grout mix optimization and construction time control in engineering practice, improving grouting effectiveness and project stability.

[0068] The viscosity of cement-based grout changes over time, mainly influenced by factors such as hydration reaction, temperature, and admixtures. The formula for calculating the exponential growth model of the time-varying viscosity of cement-based grout can be expressed as:

[0069] ;

[0070] in, express The viscosity of the slurry at any given time, expressed in Pa·s; This indicates the initial viscosity of the slurry, expressed in Pa·s. Indicates the viscosity growth rate. For time.

[0071] Step S2: Based on the obtained time-varying characteristics, construct a particle contact model of the slurry DEM; perform splitting grouting simulation based on the constructed slurry DEM particle contact model.

[0072] The construction of the slurry DEM particle contact model includes: simulation of the injected medium environment, servo-driven in-situ stress loading, slurry particle generation, assignment of inter-particle parameters, monitoring of multi-field physical information, design of time-varying initial conditions for slurry viscosity, traversal of global particle contact parameters, determination and iterative update of time-varying slurry viscosity characteristics, critical conditions for slurry phase change, and update of strength enhancement after initial setting of slurry veins. Specifically, this can be achieved through the following steps S201-S210:

[0073] Step S201: Simulation of the environment of the injected medium.

[0074] In the simulation phase of the injected medium environment, a numerical model of the porous medium that conforms to the actual geological conditions is constructed, including parameters such as soil particle distribution, porosity, and permeability.

[0075] Based on the engineering background and the properties of the injected medium in physical experiments, a numerical model of the porous medium that conforms to actual geological conditions is constructed. Specifically, the discrete element method (DEM) is used to establish the particles of the injected medium, including defining necessary attributes such as particle size, porosity, particle size distribution, contact model, and contact parameters. The injected medium particles are generated through command flow and Fish language code, so that the numerical model can accurately reflect the real formation characteristics and provide a reasonable injected medium environment for slurry diffusion.

[0076] Step S202: Servo-driven ground stress loading.

[0077] Servo-driven stress loading is performed to ensure that the stress state of the medium during the numerical simulation is consistent with the field conditions, providing a realistic stress boundary for slurry diffusion.

[0078] Furthermore, servo-controlled geostress boundary conditions are applied to the DEM model to ensure that the stress state in the computational domain is consistent with that in the field. By setting constraints on the force and deformation of boundary particles, the initial stress balance of the surrounding rock before grouting is achieved, providing a realistic stress environment for grout splitting and diffusion.

[0079] Step S203: Slurry particle generation.

[0080] In the slurry particle generation stage, slurry particles are constructed using numerical generation methods to assign appropriate contact parameters to them in their initial state.

[0081] Furthermore, DEM, known in practical applications as the particle flow method, can be formed and expressed using a combination of several particles to represent the flow characteristics of fracturing slurry in the injected medium. Initially, the slurry particles should possess fluid properties, characterized using the Hertz model. Alternatively, the JKR model, considering the attractive forces caused by the van der Waals effect, can be used. The mutual attractive forces between particles are represented by surface energy, and these forces exist only at the contact surface. This model can best characterize the contact characteristics between wet particles and is often used to represent the adhesion between wet and fine particles, ensuring that it can simulate the flow behavior of low-viscosity slurries in the initial stages.

[0082] Step S204: Assigning interparticle parameters.

[0083] The contact stiffness and viscous damping coefficient between particles are determined based on experimental data to ensure the rationality of slurry diffusion during the simulation process.

[0084] Furthermore, based on experimental data, contact parameters between grout particles and soil particles were set, including contact stiffness, viscous damping, and friction coefficient. A viscoelastic contact model was used to calculate the interaction forces between the injected medium particles, and the Hertz or JKR model was used to calculate the interaction forces between grout particles and between grout particles and the injected medium particles, ensuring accurate simulation of the rheological properties of the grout during diffusion.

[0085] The contact parameter setting method is as follows: First, query the help file of the applicable interparticle contact model, such as the Hertz model or JKR model, for the required parameter names and the value range of each parameter. Second, based on the physical test results such as the cement paste funnel flowability test, cement paste plate flowability test, and time-varying viscosity paddle rotor test, use a trial-and-error method to ensure that the numerical test results under a certain working condition are consistent with the physical test results. At this point, the adopted contact parameters can be considered scientifically reasonable.

[0086] Step S205: Multi-field physical information monitoring.

[0087] Multiple physical information monitoring was conducted, and the detected physical information included changes in grout pressure, grout volume, and porosity between injected media during the grout diffusion process, which provided data support for subsequent analysis.

[0088] Furthermore, during the DEM calculation process, the internal pressure of the grout particles and the grout injection volume were monitored in real time, and parameters such as the porosity change in the injected medium were monitored by measuring the circle. Combined with stress distribution and crack propagation, the splitting diffusion path and filling degree of the grout in the medium were analyzed, providing a scientific basis for the study of the grout diffusion reinforcement mechanism.

[0089] Step S206: Design of time-varying initial conditions for slurry viscosity.

[0090] In the initial condition design stage of time-varying slurry viscosity, the slurry viscosity variation curve over time is set based on experimental data and assigned values ​​in numerical calculations.

[0091] Furthermore, based on different grouting processes (orifice mixing, bottom mixing, etc.), initial triggering conditions for the time-varying viscosity of the grout are set. User-defined functions (using the Fish language) are written to determine the initial determination and triggering conditions for the evolution of the rheological parameters of the grout particles over time.

[0092] Step S207: Traverse the global particle contact parameters.

[0093] When traversing the global particle contact parameters, the interaction forces between particles are gradually adjusted through trial and error by relying on the contact parameter assignment command of the discrete element method to simulate the diffusion pattern of slurry in porous media.

[0094] Furthermore, by employing parameter sensitivity analysis, key parameters such as contact stiffness, shear strength, and viscosity coefficient were sequentially adjusted in the DEM calculation to ensure that the simulated diffusion state of the slurry at different stages matched the actual situation, and the model parameters were optimized to improve simulation accuracy.

[0095] Step S208: Determination and iterative update of time-varying characteristics of slurry viscosity.

[0096] The time-varying characteristics of grout viscosity are determined and iteratively updated. Based on the grout flow state and shear stress conditions, the grout viscosity parameters are dynamically adjusted to make the simulation results consistent with the actual grouting process.

[0097] Furthermore, based on conditions such as shear stress, flow velocity, and temperature, the trend of slurry viscosity change is determined, and the interparticle viscosity damping coefficient is dynamically adjusted. Combining the time-varying effect curve of slurry viscosity, a time-step control algorithm is employed to make the slurry viscosity evolve over time, ensuring that the simulation results match the actual situation.

[0098] Step S209: Setting critical conditions for slurry phase change.

[0099] The critical conditions for phase change of slurry are mainly based on the initial setting time and rheological properties of slurry to ensure that the slurry gradually completes the transformation from fluid to solid during the diffusion process.

[0100] Furthermore, based on the gelation time and phase transition characteristics of the slurry, a threshold condition for the abrupt change of interparticle forces over time is set. When the viscosity reaches the phase transition point, the interparticle contact stiffness and shear strength are gradually adjusted to allow the slurry to transition from a fluid to a solid state and form a slurry vein structure.

[0101] Step S210: Strength enhancement and update after initial coagulation of the slurry vein.

[0102] In the strength enhancement and renewal stage after the initial setting of the slurry vein, the particle contact parameters are adjusted by considering the mechanical properties of the slurry after solidification, so as to reflect the improvement of the load-bearing capacity of the slurry vein after solidification and ensure that the model can accurately describe the entire process of slurry diffusion and solidification.

[0103] Furthermore, after solidification, the particle contact model is adjusted through parameter settings or code commands to improve contact stiffness, friction coefficient, and tensile strength, thereby simulating the load-bearing capacity after consolidation. Combined with experimental data, the mechanical parameters of the grout veins are corrected to ensure that the numerical model accurately reflects the reinforcement effect of fracturing grouting.

[0104] Steps S201-S210 are interconnected and together construct a simulation system that realistically restores the splitting grouting process considering the time-varying characteristics of grout viscosity.

[0105] Step S3: Under fixed working conditions, compare the simulation results obtained from the split grouting simulation with the test results from the indoor test, and calibrate the grout DEM particle contact model based on the comparison results.

[0106] Under fixed working conditions, the final morphology of the splitting diffusion in experiments and simulations is compared and verified with the physical and mechanical properties of the grouting solid. The experimental results obtained from indoor tests include morphological results, physical property results, and mechanical property results. Specifically, the simulation results are compared with the final morphological results from physical tests, such as the direction and range of the splitting grout diffusion and channel tension, as well as with the test results of physical properties such as the impermeability of the grouting solid and mechanical properties such as triaxial compressive strength or direct shear strength. This can be achieved through the following steps S301-S303:

[0107] Step S301: Comparison and verification of the diffusion morphology of splitting slurry.

[0108] Under a fixed working condition in the physical experiment, the results of the indoor or field high-pressure fracturing grouting test are observed to obtain the morphology of grout fracturing and diffusion, and to measure the development direction, maximum diffusion range, and average width of the grout vein. By comparing the simulation results, it is determined whether the directionality, consistency, and spatial distribution of grout fracturing and diffusion in the simulation are consistent with the physical experiment, thereby verifying the rationality of the numerical simulation.

[0109] As an optional implementation, in physical experiments, the direction, range, and channel tension of grout diffusion are obtained through high-pressure fracturing grouting tests, and the grout vein morphology is measured using profile cutting or CT scanning techniques. In numerical simulation, the grout diffusion path, maximum diffusion radius, and grout vein morphology parameters are extracted, and the simulation results are compared with experimental data to determine whether the fracturing directionality, consistency, and spatial distribution match. If deviations occur, the time-varying grout viscosity model or particle contact parameters are adjusted to optimize the numerical model and improve the reliability of the simulation.

[0110] Step S302: Comparison and verification of the physical properties of the grouting solidified material, such as its impermeability.

[0111] Regarding the overall physical properties of the grouting solid, the tests mainly include indicators such as permeability and density. The permeability coefficient of the grouting solid is measured by a permeability test and compared with the simulation results to determine whether the simulation results are similar to the physical test results in terms of the physical properties of the solid.

[0112] As an optional embodiment, physical testing employs permeability testing to measure the permeability coefficient of the solidified material and evaluate its density, microstructure, and other characteristics. In numerical simulation, permeability coefficients are calculated using seepage analysis, and the pore distribution after slurry consolidation is simulated. By comparing the permeability coefficients and flow field distributions obtained from experiments and simulations, the accuracy of the simulation results in terms of impermeability is determined. If necessary, the parameters of the solidification stage are optimized to match the physical properties of the actual solidified material.

[0113] Step S303: Comparison and verification of mechanical properties such as triaxial compressive strength or direct shear strength.

[0114] In terms of mechanical properties, the strength and deformation characteristics of the reinforced body are evaluated through triaxial compression tests or direct shear tests. The key parameters such as peak strength, deformation modulus, and shear strength obtained from the tests are compared with the simulated values ​​to analyze the accuracy of the numerical model in terms of stress-strain response.

[0115] As an optional implementation, physical tests employ triaxial compression or direct shear tests to determine parameters such as the strength, deformation modulus, and shear strength of the reinforced body. Numerical simulations obtain stress-strain curves, peak strength, and shear failure modes through mechanical calculations. The accuracy of the simulation in terms of the mechanical properties of the reinforced body is analyzed by comparing experimental data with simulation results. If discrepancies exist, the slurry solidification model or particle contact stiffness parameters are adjusted to optimize the mechanical response of the numerical simulation.

[0116] Through various tests in steps S301-S303, the simulation method can be verified to ensure that it can realistically reflect the actual diffusion behavior and reinforcement effect of fracturing grouting, thereby improving the reliability of the simulation results.

[0117] Step S4: Using the calibrated grout DEM particle contact model, perform fracturing grouting simulation under multiple working conditions.

[0118] Numerical simulation of fracturing and diffusion under extended working conditions. Based on the numerical model verified in step S3, simulations of grout fracturing and diffusion under more extended working conditions are conducted; among them, the extended multi-working conditions include in-situ stress conditions, grouting pressure, and grout mix ratio, etc.

[0119] After comparing and verifying the physical test and simulation results under certain working conditions, it is believed that the established discrete element contact model of the grout can accurately reflect the grout splitting and diffusion process. Based on this model, further simulation studies under extended working conditions can be carried out under different geostress field distributions, surrounding rock properties, time-varying grout viscosity characteristics, and grouting pressures. The influence of different environmental variables on the grout diffusion range, grout vein morphology, and reinforcement effect can be analyzed. In the extended working condition simulation, by adjusting the numerical model parameters, the flow trend, splitting path, and termination diffusion range of the grout under different grouting pressures can be predicted, thereby optimizing the splitting grouting design under different geological conditions and improving the construction adaptability and engineering safety in complex environments. Specifically, this can be achieved through the following steps S401-S402:

[0120] S401, Extended operating condition simulation based on the verification model.

[0121] After verifying and checking the contact parameters in step S3, the established numerical model for grout fracturing and diffusion can be used for simulation studies under different working conditions. By adjusting key parameters such as the in-situ stress field, grouting pressure, and grout mix ratio, their influence on the grout diffusion range, fracturing path, and reinforcement effect can be analyzed. For example, under different surrounding rock strength or permeability conditions, the study investigates how the grout penetrates, expands, and solidifies, revealing the sensitive factors of grout diffusion. This process helps to understand the fracturing grouting mechanism under complex geological conditions and provides a scientific basis for further design optimization.

[0122] S402, Engineering Applications and Optimization Design.

[0123] Extended working condition simulation not only helps reveal the diffusion law of grout but also provides guidance for practical engineering. By simulating the diffusion characteristics under different grouting parameters, grouting pressure, grout parameters, and mix proportions can be optimized to improve reinforcement effects and reduce grout loss. Furthermore, in projects such as tunnel surrounding rock reinforcement, slope treatment, and mine backfilling, numerical simulation can be used to predict the grouting range, optimize construction techniques, improve construction efficiency and safety, thereby reducing engineering risks and achieving refined grouting design.

[0124] like Figure 2 As shown in the figure, the time-varying parameters of the splitting grout viscosity are obtained by the discrete element numerical simulation method based on the time-varying characteristics of grout viscosity. It can be seen that:

[0125] 1) The existence environment of the pore-injected medium 1 under in-situ stress conditions was simulated and recreated under the constraints of biaxial geostress (i.e., vertical geostress servo loading boundary 2 and horizontal geostress servo loading boundary 3). Among them, the surface viscosity parameter 6 between the grout particles moves downward in the splitting grout injection channel 5 within the grouting pipe boundary 4, and after leaving the grout outlet 7, it develops in the splitting grout development direction 8 (the direction of the major principal stress).

[0126] 2) The time-varying viscosity characteristics between slurry particles are illustrated using the surf_adh parameter in the JKR contact model as an example. Figure 2 In the middle, the right side is a schematic diagram of the surface energy contact parameter values. The darker the color (closer to black), the closer the surface energy contact parameter is to 16, and the lighter the color (closer to white), the closer the surface energy contact parameter is to 0.

[0127] This shows that the slurry viscosity is relatively low (tending towards its initial viscosity) near the point where the slurry particles leave the grouting pipe, and gradually increases as the diffusion time increases (as the particles move further away from the grouting pipe). This demonstrates that the time-varying effect of slurry viscosity has been effectively simulated.

[0128] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0129] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity, characterized in that, include: Indoor tests were conducted on the time-varying characteristics of slurry viscosity, and the time-varying characteristics of slurry viscosity were obtained based on the test results. Based on the obtained time-varying characteristics, a particle contact model of the slurry DEM was constructed; The fracturing grouting simulation was carried out based on the established grout DEM particle contact model. The construction of the grout DEM particle contact model includes: simulation of the injected medium environment, servo stress loading, grout particle generation, particle parameter assignment, multi-field physical information monitoring, design of time-varying initial conditions for grout viscosity, traversal of global particle contact parameters, determination and iterative update of time-varying characteristics of grout viscosity, critical conditions for grout phase change and update of strength improvement after initial setting of grout veins. Under fixed working conditions, the simulation results obtained from the split grouting simulation were compared with the test results from the laboratory test, and the grout DEM particle contact model was calibrated based on the comparison results. Using the calibrated grout DEM particle contact model, we conducted multi-condition fracturing grouting simulation.

2. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 1, characterized in that, The indoor tests include: cement paste funnel flowability test, cement paste plate flowability test, and slurry viscosity time-varying characteristic paddle rotor test.

3. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 2, characterized in that: In the test of cement paste flowability in a funnel, the change in the time it takes for the paste to flow out of a standard funnel characterizes the viscosity growth. In the cement paste plate fluidity test, the limiting effect of slurry viscosity growth on the spread is obtained by measuring the spread diameter of the slurry on the plate. In the time-varying viscosity test of the paddle rotor, the viscosity change curve of the slurry over time is plotted by measuring the shear viscosity of the slurry at different time points.

4. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 1, characterized in that, Based on the simulation of the injected medium environment, a numerical model of porous media that conforms to the actual geological conditions is constructed. During the multi-field physical information monitoring process, the detected physical information includes the changes in grout pressure, grout volume, and porosity between injected media during the grout diffusion process.

5. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 1, characterized in that: When traversing the global particle contact parameters, the interparticle forces are gradually adjusted using the trial-and-error method based on the contact parameter assignment command of the discrete element method to simulate the diffusion pattern of slurry in porous media. The determination and iterative update of the time-varying characteristics of grout viscosity involves dynamically adjusting the grout viscosity parameters based on the grout flow state and shear stress conditions to ensure that the simulation results match the actual grouting process.

6. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 1, characterized in that, The critical condition for phase change of slurry is set based on the initial setting time and rheological properties of the slurry.

7. The discrete element numerical simulation method for splitting grouting based on time-varying slurry viscosity as described in claim 1, characterized in that, Under fixed working conditions, the simulation results obtained from the splitting grouting simulation are compared with the test results from the laboratory test; the test results obtained from the laboratory test include morphological results, physical property results and mechanical property results.

8. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 7, characterized in that: The morphological results obtained are as follows: Under the fixed working conditions in the physical test, the results of the high-pressure splitting grouting test are observed to obtain the morphology of grout splitting and diffusion, and the development direction, maximum diffusion range and average width of grout veins of grout splitting and diffusion are measured. The obtained physical properties results are as follows: the overall physical properties of the grouting solidified body were tested, including permeability and density; The obtained mechanical properties are as follows: the strength and deformation characteristics of the reinforced body are evaluated using triaxial compression tests and direct shear tests.

9. The discrete element numerical simulation method for splitting grouting based on the time-varying characteristics of grout viscosity as described in claim 1, characterized in that, The multiple working conditions include ground stress conditions, grouting pressure, and grout mix ratio.

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